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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning Blog

AWS provides a powerful set of tools and services that simplify the process of building and deploying generative AI applications, even for those with limited experience in frontend and backend development. The AWS deployment architecture makes sure the Python application is hosted and accessible from the internet to authenticated users.

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Snorkel AI signs strategic collaboration agreement with AWS to help enterprises cross the demo-to-production chasm

Snorkel AI

AWS provides a robust framework for responsible AI development with Amazon SageMaker, a fully managed service that brings together a broad set of tools to build, train, and deploy generative AI and machine learning (ML) models. Our relationship with AWS helps organizations around the globe accelerate the demo-to-production pipeline.

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AWS at NVIDIA GTC 2024: Accelerate innovation with generative AI on AWS

AWS Machine Learning Blog

AWS was delighted to present to and connect with over 18,000 in-person and 267,000 virtual attendees at NVIDIA GTC, a global artificial intelligence (AI) conference that took place March 2024 in San Jose, California, returning to a hybrid, in-person experience for the first time since 2019.

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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. Third, we’ll explore the robust infrastructure services from AWS powering AI innovation, featuring Amazon SageMaker , AWS Trainium , and AWS Inferentia under AI/ML, as well as Compute topics.

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Snorkel AI joins the AWS ISV Accelerate Program and launches Snorkel Flow Availability in AWS Marketplace

Snorkel AI

That’s why at Snorkel AI, we believe data is the true differentiator, a vision we share with Amazon Web Services (AWS). In June, Snorkel and AWS signed a multi-year strategic collaboration agreement to help enterprises build, deploy, and evaluate custom, production-ready AI models.

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Architecture to AWS CloudFormation code using Anthropic’s Claude 3 on Amazon Bedrock

AWS Machine Learning Blog

Architecting specific AWS Cloud solutions involves creating diagrams that show relationships and interactions between different services. Instead of building the code manually, you can use Anthropic’s Claude 3’s image analysis capabilities to generate AWS CloudFormation templates by passing an architecture diagram as input.

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Snorkel AI signs strategic collaboration agreement with AWS to help enterprises cross the demo-to-production chasm

Snorkel AI

AWS provides a robust framework for responsible AI development with Amazon SageMaker, a fully managed service that brings together a broad set of tools to build, train, and deploy generative AI and machine learning (ML) models. Our relationship with AWS helps organizations around the globe accelerate the demo-to-production pipeline.

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